Evidence map›Paper›PMID 41691061›Full record

ArticleBritish journal of cancer2026

A digital quality measure for emergency presentation of pancreatic cancer.

Natalia Khalaf, Gabriel Sandoval, Andrew J Zimolzak, Paarth Kapadia, Yan Liu, Hardeep Singh

Abstract read
In one paragraph

Article in British journal of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Natalia KhalafCenter for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, USA. natalia.khalaf@bcm.edu.ORCID http://orcid.org/0000-0002-7585-6183
Gabriel SandovalSection of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Andrew J ZimolzakCenter for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, USA.
Paarth KapadiaDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA.
Yan LiuCenter for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, USA.
Hardeep SinghCenter for Innovations in Quality, Effectiveness and Safety (IQuESt), Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, USA.

Funding

AHRQ HHS R01 HS028595AHRQ HHS R18 HS029347Gordon and Betty Moore Foundation (Gordon E. and Betty I. Moore Foundation) GBMF11505Health Services Research and Development (VA Health Services Research and Development Service) 1 IK2 HX003346-01A2Health Services Research and Development (VA Health Services Research and Development Service) CIN13-413
6 · The paper itself

Abstract

backgroundOver half of patients with pancreatic cancer experience an emergency cancer diagnosis, but tools for large-scale study are lacking. Towards this end, we developed a digital quality measure (dQM) to automate the detection of pancreatic cancer emergency presentations (EPs).

methodsA dQM for pancreatic cancer EPs was developed within the U.S. Veterans Affairs health care system. Multivariable regression models were used to study the associations between EPs and cancer outcomes. Records of EP cases were manually reviewed to identify missed opportunities in diagnosis.

resultsThe dQM had a positive predictive value of 86.4% (95% CI 80.0-92.8) for accurately identifying EPs among patients with pancreatic cancer. Among 4415 pancreatic cancer patients, 60.9% were identified as EPs by the measure. Patients with EPs had more advanced-stage disease (adjusted OR 1.38; 95% CI 1.20-1.59) and higher mortality (adjusted HR 1.64; 95% CI 1.51-1.77). Nearly one in five EP cases had missed opportunities in diagnosis.

conclusionsOur dQM had strong performance characteristics for identifying pancreatic cancer EPs, which were independently associated with worse patient outcomes. A notable subset of cases was potentially avoidable. The dQM is a promising strategy for health care systems to identify and measure EPs for quality improvement initiatives.

Indexed as

Pancreatic NeoplasmsAgedFemaleHumansMaleMiddle AgedQuality Indicators, Health CareUnited States

Identifiers

PMID41691061
PMCPMC13035855

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.